# openacid/slim

Surprisingly space efficient trie in Golang(11 bits/key; 100 ns/get).

Repository: https://github.com/openacid/slim
Canonical: https://ross.abutalabs.com/products/openacid-slim
Homepage: https://openacid.github.io/
Language: Go
License: MIT
License Family: permissive
Topics: go, golang, memory, compacted, compress, datastructure, trie, tree
Last push: 2026-08-24T02:16:22+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 2769, "days_push": 10, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1923, forks 100 (observed 2026-08-28T04:05:55.323101+00:00)

## What it is
Slim is a Go library providing space-efficient data structures, most notably SlimTrie, a compacted trie that uses only about 11 bits per key with ~100 ns lookups. It serves as a minimized in-memory index for locating data stored externally on disk or over the network, with serialization support for persistence and transport.

## Use cases
- index huge on-disk key-value stores with minimal memory
- build a sparse in-memory index over external data
- perform range scans over sorted keys with low memory overhead
- store a compact set of keys as a filter in memory
- persist a compact index to disk or serialize it for transport
- reduce memory footprint of key lookup structures in Go services

## When to choose
- you need to index millions or billions of keys in limited memory
- your data lives on disk and you only need to know where it is
- you want a faster, more compact alternative to hash maps or B-trees for static key sets
- you need a serializable, stable-memory index structure in Go

## When to avoid
- your key set changes frequently, since the trie is built for mostly static data
- you need rich per-key values stored in memory rather than just locations
- you are not working in Go
- you need dynamic insert/delete-heavy workloads with guaranteed latency

## Facets
- artifact type: library
- maturity: stable
- function: search-engine, serialization, developer-tools
- domain: databases, performance, developer-tools
- platform: go, cross-platform
- tags: trie, compact-data-structures, memory-efficient, index, key-value, algorithms

## Member repositories
- openacid/slim (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:55.323101+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:09:38.980098+00:00, confidence not recorded.
  - readme: https://github.com/openacid/slim (fetched 2026-08-28T04:05:55.323101+00:00, sha fd4b87dd05ae)
  - homepage: https://openacid.github.io/ (fetched 2026-08-29T10:48:59.388325+00:00, sha a841b0a78368)
- Data as of 2026-08-30T08:39:29.467469+00:00.